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setup.py
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#!/usr/bin/env python
import os, sys
import shutil
import datetime
from setuptools import setup, find_packages
from setuptools.command.install import install
# readme = open('README.md').read()
readme = """
# Once for All: Train One Network and Specialize it for Efficient Deployment [[arXiv]](https://arxiv.org/abs/1908.09791) [[Slides]](https://file.lzhu.me/projects/OnceForAll/OFA%20Slides.pdf) [[Video]](https://youtu.be/a_OeT8MXzWI)
```BibTex
@inproceedings{
cai2020once,
title={Once for All: Train One Network and Specialize it for Efficient Deployment},
author={Han Cai and Chuang Gan and Tianzhe Wang and Zhekai Zhang and Song Han},
booktitle={International Conference on Learning Representations},
year={2020},
url={https://arxiv.org/pdf/1908.09791.pdf}
}
```
## News
- Fisrt place in the 4th [Low-Power Computer Vision Challenge](https://lpcv.ai/competitions/2019), both classification and detection track.
- First place in the 3rd [Low-Power Computer Vision Challenge](https://lpcv.ai/competitions/2019), DSP track at ICCV’19 using the Once-for-all Network.
## Check our [GitHub](https://github.com/mit-han-lab/once-for-all) for more details.
"""
VERSION = "0.1.0"
requirements = [
"torch",
]
# import subprocess
# commit_hash = subprocess.check_output("git rev-parse HEAD", shell=True).decode('UTF-8').rstrip()
# VERSION += "_" + str(int(commit_hash, 16))[:8]
VERSION += "_" + datetime.datetime.now().strftime("%Y%m%d%H%M")
# print(VERSION)
setup(
# Metadata
name="ofa",
version=VERSION,
author="MTI HAN LAB ",
author_email="[email protected]",
url="https://github.com/mit-han-lab/once-for-all",
description="Once for All: Train One Network and Specialize it for Efficient Deployment.",
long_description=readme,
long_description_content_type="text/markdown",
license="MIT",
# Package info
packages=find_packages(exclude=("*test*",)),
#
zip_safe=True,
install_requires=requirements,
# Classifiers
classifiers=[
"Programming Language :: Python :: 3",
],
)